Detection of neuronal loss using T MRI assessment of 1H2O spin dynamics in the aphakia mouse

Shalom Michaeli, Terry C. Burns, Elina Kudishevich, Noam Harel, Tim Hanson, Dennis J. Sorce, Michael Garwood, Walter C. Low

Research output: Contribution to journalArticlepeer-review

12 Scopus citations


The loss of dopaminergic (DA) neurons in the substantia nigra pars compacta (SNc) is well characterized in Parkinson's disease (PD). Recent developments in magnetic resonance imaging (MRI) techniques have provided the opportunity to evaluate for changes in cellular density. Longitudinal relaxation measurements in the rotating frame (T) provide a unique magnetic resonance imaging contrast in vivo. Due to the specificity of T to water-protein interactions, the T MRI method has strong potential to be used as a non-invasive method for quantification of neuronal density in the brain. Recently introduced adiabatic T magnetic resonance imaging mapping methods provide a tool to assess molecular motional regimes with high sensitivity due to utilization of an effective magnetic field sweep during adiabatic pulses. In this work, to investigate the sensitivity of T to alterations in neuronal density, adiabatic T MRI measurements were employed in vivo on Pitx3-homeobox gene-deficient aphakia mice in which the deficit of DA neurons in the SNc is well established. The theoretical analysis of T maps in the different areas of the brain of aphakia mouse suggested variation of the 1H2O rotational correlation times, τc. This suggests τc to be a sensitive indicator for neuronal loss during neurological disorders. The results manifest significant dependencies of the T relaxations on the cell densities in the SNc, suggesting T MRI method as a candidate for detection of neuronal loss in neurological disorders.

Original languageEnglish (US)
Pages (from-to)160-167
Number of pages8
JournalJournal of Neuroscience Methods
Issue number1
StatePublished - Feb 15 2009


  • Neuronal loss
  • Substantia nigra pars compacta
  • T MRI

ASJC Scopus subject areas

  • General Neuroscience


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